Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Tomtebodavägen 18 A, 10th Floor, Solna, 171 65, Stockholm, Sweden.
Stockholm Gerontology Research Center, Stockholm, Sweden.
Sci Rep. 2023 Mar 2;13(1):3543. doi: 10.1038/s41598-023-30350-3.
The prompt identification of frailty in primary care is the first step to offer personalized care to older individuals. We aimed to detect and quantify frailty among primary care older patients, by developing and validating a primary care frailty index (PC-FI) based on routinely collected health records and providing sex-specific frailty charts. The PC-FI was developed using data from 308,280 primary care patients ≥ 60 years old part of the Health Search Database (HSD) in Italy (baseline 2013-2019) and validated in the Swedish National Study on Aging and Care in Kungsholmen (SNAC-K; baseline 2001-2004), a well-characterized population-based cohort including 3363 individuals ≥ 60 years old. Potential health deficits part of the PC-FI were identified through ICD-9, ATC, and exemption codes and selected through an optimization algorithm (i.e., genetic algorithm), using all-cause mortality as the main outcome for the PC-FI development. The PC-FI association at 1, 3 and 5 years, and discriminative ability for mortality and hospitalization were tested in Cox models. The convergent validity with frailty-related measures was verified in SNAC-K. The following cut-offs were used to define absent, mild, moderate and severe frailty: < 0.07, 0.07-0.14, 0.14-0.21, and ≥ 0.21. Mean age of HSD and SNAC-K participants was 71.0 years (55.4% females). The PC-FI included 25 health deficits and showed an independent association with mortality (hazard ratio range 2.03-2.27; p < 0.05) and hospitalization (hazard ratio range 1.25-1.64; p < 0.05) and a fair-to-good discriminative ability (c-statistics range 0.74-0.84 for mortality and 0.59-0.69 for hospitalization). In HSD 34.2%, 10.9% and 3.8% were deemed mildly, moderately, and severely frail, respectively. In the SNAC-K cohort, the associations between PC-FI and mortality and hospitalization were stronger than in the HSD and PC-FI scores were associated with physical frailty (odds ratio 4.25 for each 0.1 increase; p < 0.05; area under the curve 0.84), poor physical performance, disability, injurious falls, and dementia. Almost 15% of primary care patients ≥ 60 years old are affected by moderate or severe frailty in Italy. We propose a reliable, automated, and easily implementable frailty index that can be used to screen the primary care population for frailty.
在初级保健中及时识别虚弱是为老年人提供个性化护理的第一步。我们旨在通过开发和验证基于常规健康记录的初级保健虚弱指数(PC-FI)并提供性别特异性虚弱图表,来检测和量化初级保健老年患者的虚弱程度。PC-FI 是使用意大利健康搜索数据库(HSD)中 308280 名≥60 岁的初级保健患者的数据(基线 2013-2019 年)开发的,并在瑞典老年和 Kungsholmen 护理研究(SNAC-K;基线 2001-2004 年)中进行了验证,这是一个特征明确的基于人群的队列,包括 3363 名≥60 岁的个体。通过 ICD-9、ATC 和豁免代码确定潜在的健康缺陷,并通过优化算法(即遗传算法)选择 PC-FI 开发的潜在健康缺陷,使用全因死亡率作为 PC-FI 开发的主要结果。在 Cox 模型中测试了 PC-FI 在 1、3 和 5 年的相关性以及对死亡率和住院的判别能力。在 SNAC-K 中验证了与虚弱相关措施的收敛效度。使用以下截止值来定义无、轻度、中度和重度虚弱:<0.07、0.07-0.14、0.14-0.21 和≥0.21。HSD 和 SNAC-K 参与者的平均年龄为 71.0 岁(55.4%为女性)。PC-FI 包含 25 个健康缺陷,与死亡率(危险比范围 2.03-2.27;p<0.05)和住院率(危险比范围 1.25-1.64;p<0.05)独立相关,并具有良好的判别能力(死亡率的 C 统计量范围为 0.74-0.84,住院率为 0.59-0.69)。在 HSD 中,分别有 34.2%、10.9%和 3.8%的患者被认为是轻度、中度和重度虚弱。在 SNAC-K 队列中,PC-FI 与死亡率和住院率的相关性强于 HSD,PC-FI 评分与身体虚弱(每增加 0.1 分的优势比为 4.25;p<0.05;曲线下面积为 0.84)、身体机能差、残疾、受伤跌倒和痴呆症相关。意大利约有 15%的≥60 岁的初级保健患者患有中度或重度虚弱。我们提出了一种可靠、自动化和易于实施的虚弱指数,可以用于筛选初级保健人群的虚弱程度。